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Paul Brennan
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MS18 - Role of Biomarkers in Lung Cancer Screening (ID 81)
- Event: WCLC 2019
- Type: Mini Symposium
- Track: Screening and Early Detection
- Presentations: 1
- Now Available
- Moderators:Luis M Montuenga, Luis M Seijo
- Coordinates: 9/10/2019, 14:30 - 16:00, Vancouver (2003)
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MS18.03 - Amolecular Diagnostics, Incorporating GWAS and Risk Models: Future Approaches to the Identification of High-Risk Individuals (Now Available) (ID 3546)
14:30 - 16:00 | Presenting Author(s): Paul Brennan
- Abstract
- Presentation
Abstract
Role of Biomarkers in Lung Cancer Screening
As a part of ongoing research to understand the etiology and early detection of lung cancer, the Integrative Analysis of Lung Cancer Etiology and Risk (INTEGRAL) consortium has been genotyping large numbers of lung cancer cases and controls and analyzing biomarkers from case cohort members prior to their diagnosis with lung cancer and matched controls. We are also assembling knowledge about predictors of lung cancer risk to identify biomarkers that will be applied along with radiomic features to select individuals at highest risk for lung cancer to enroll in screening studies and to assist in resolution of cancer risk among those found to have small nodules. To date we have analyzed genetic data from 29,266 patients and 56,450 controls of European descent(1) and curated genotyping information from 20 studies conducted in European descent, 14 from Asian descent and 1 study in African-American Populations(2). Ongoing imputation is allowing us to integrate most of these data for a further analysis that brings together world populations for genetic discovery. Results of these studies have identified 12 strongly replicated loci and an additional 38 loci that are highly significant in some studies but less well replicated. Among the variants that we identified, a variant in BRCA2 (1) is remarkable for conferring over 2 fold increased risk for lung cancer development independent of smoking behavior and thereby indicating a small subset of high risk individuals based on genotype. Further studies to identify rare variants that confer a high risk of lung cancer have identified mutations in ATM and KIAA0930 with odds ratios well over 2. The ATM variant is associated with loss of heterozygosity in tumors but does not cause Ataxia Telangiectasia in homozygotes. We have used genetic information to develop polygenic risk scores and a model that included 221 variants yielded the most improvement in accuracy. Results comparing models to identify individuals at high risk for lung cancer development based on risk scores compared with models based on demographic, clinical and smoking information show a modest increase in prediction accuracy, but identify selected individuals who are at high risk and for whom lung screening would be particularly indicated.
The genetic information we have developed and curated can also be used with additional approaches to identify predictors of lung cancer risk using shared heritability and Mendelian randomization analyses. Shared heritability analysis identifies strong genetic correlations with all measures of smoking behavior and also with primary biliary cirrhosis and schizophrenia. Mendelian randomization, which removes concerns about change in BMI during cancer development, shows that increased BMI is associated with squamous and small cell lung cancer and not associated with adenocarcinoma(3). Mendelian randomization studies found association of increased lung cancer risk with longer germline telomere length and increased risk associated with higher levels of vitamin B12(4). Further Mendelian randomization studies are underway to evaluate other biochemical factors that may associate with increased lung cancer risk.
Cohort studies to identify biomarker signatures of risk have identified a reliable panel(5) comprising CEA125, CEA, CYFRA 21-1 and pro-SFTB that along with smoking behavior provide an area under the receiver operator curve of 83%, indicating that a strategy that seeks to identify high risk individuals using data from questionnaires about smoking along with biomarker analysis could substantially improve the yield of low dose spiral CT screening. Further studies of panels of biomarkers including microRNA and circulating cell-free DNA are underway to evaluate the utility of adding additional biomarkers to further identify higher risk individuals.
1. McKay JD, et al. (2017) Large-scale association analysis identifies new lung cancer susceptibility loci and heterogeneity in genetic susceptibility across histological subtypes. Nature genetics 49(7):1126-1132.
2. Bosse Y & Amos CI (2018) A Decade of GWAS Results in Lung Cancer. Cancer epidemiology, biomarkers & prevention : a publication of the American Association for Cancer Research, cosponsored by the American Society of Preventive Oncology 27(4):363-379.
3. Carreras-Torres R, et al. (2017) Obesity, metabolic factors and risk of different histological types of lung cancer: A Mendelian randomization study. PloS one 12(6):e0177875.
4. Fanidi A, et al. (2018) Is high vitamin B12 status a cause of lung cancer? International journal of cancer. Journal international du cancer.
5. Integrative Analysis of Lung Cancer E, et al. (2018) Assessment of Lung Cancer Risk on the Basis of a Biomarker Panel of Circulating Proteins. JAMA oncology 4(10):e182078.
Only Members that have purchased this event or have registered via an access code will be able to view this content. To view this presentation, please login, select "Add to Cart" and proceed to checkout. If you would like to become a member of IASLC, please click here.
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P1.11 - Screening and Early Detection (ID 177)
- Event: WCLC 2019
- Type: Poster Viewing in the Exhibit Hall
- Track: Screening and Early Detection
- Presentations: 1
- Moderators:
- Coordinates: 9/08/2019, 09:45 - 18:00, Exhibit Hall
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P1.11-36 - A Simple Tool to Prioritize US Ever-Smokers for CT Screening Eligibility Assessment (ID 1233)
09:45 - 18:00 | Author(s): Paul Brennan
- Abstract
Background
CT lung cancer screening can be more efficient when risk models are used to determine eligibility. However, detailed risk assessment requires time spent by a healthcare provider and may present a barrier to screening when resources are limited. Here, we developed a tool to identify ever-smokers with low probability of risk-based eligibility.
Method
We analyzed ever-smokers aged 50-80 in the representative 2015 US National Health Interview Survey. We defined ever-smokers with 6-year risk ≥1.3% by the 12-question PLCOm2012 model as screening-eligible. We considered that detailed risk assessment may be inefficient when the probability of eligibility is less than 5%. Accordingly, we used cross-tabulations of age, cigarettes-per-day, and quit-years to identify groups in whom risk assessment might be avoided.
Result
There are approximately 44,140,774 U.S. ever-smokers aged 50-80 who could consider detailed risk assessment. However, a simple decision-tree tool identified 22,293,477 ever-smokers (50.5%) who are less than 5% likely to be screening-eligible (Figure). This includes all those who smoke(d) less than 5 cigarettes-per-day. Over 1 year, approximately 103,512 lung cancers were predicted among eligible ever-smokers. If our tool were used, then 1,784 of these eligible cases (1.7%) would not undergo detailed risk assessment or screening.
Conclusion
When resources are limited, a simple decision-tree tool could avoid detailed risk assessment for more than half of U.S. ever smokers aged 50-80, while still identifying 98.3% of eligible cases. Such a tool could be self-administered by patients in the waiting room or applied automatically to electronic health records to optimize use of provider time.
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P2.03 - Biology (ID 162)
- Event: WCLC 2019
- Type: Poster Viewing in the Exhibit Hall
- Track: Biology
- Presentations: 1
- Now Available
- Moderators:
- Coordinates: 9/09/2019, 10:15 - 18:15, Exhibit Hall
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P2.03-18 - Pathogenic Germline Rare Variants and Risk of Lung Cancer (Now Available) (ID 2699)
10:15 - 18:15 | Author(s): Paul Brennan
- Abstract
Background
Recent studies suggest that rare variants, with minor allele frequencies (MAFs) of less than 0.01, exhibit stronger effect sizes than common variants, might play a crucial role in the etiology of complex traits and could account for missing heritability unexplained by common variants.
Method
Germline DNA from 1059 lung cancer cases and 899 controls from the Transdisciplinary Research in Cancer of the Lung and International Lung Cancer Consortium study were sequenced, utilizing the Agilent SureSelect XT Custom ELID and Whole Exome v5 capture. To unveil the inherited rare causal variants, allelic association analysis of single variant and gene-based collapsing tests of multiple variants were performed, including variants per gene association test, the Kernel-based adaptive cluster test, and SNP-set Kernel association test. Odds ratio (OR), 95% confidence intervals (CIs), and false discovery rate (FDR) adjusted P values were calculated.
Result
Conclusion
We identified 32 highly deleterious rare heterozygotes, including 14 rare and 18 novel variants -- absent from prior databases of genetic variation (Table 1). The top candidate substitutions including NEBstop gain p.Q7971* (nine cases versus zero control carriers, P = 0.0056), OGG1 upstream Chr 3:9816129(11 cases versus one control carriers, P = 0.0087),CDKN2B transcription end site (16 cases versus three controls carriers, P = 0.0081), ATP6V0A2 regulatory Chr 12:124242486 (eight cases versus zero control carriers, P = 0.0089), KCNN4 transcription factor binding site (15 cases versus two controls carriers, P = 0.0044), and TEX28P1 regulatory rs1445670979 (11 cases versus one control carriers, P = 0.0087). We also identified candidates in known genes which have been previously implicated in lung cancer risk, i.e., HLA, TP53, POT1, PTEN, ERC, GPC, RGS17, and LAMC1. Among the candidate genes with multiple rare deleterious SNVs, the top five genes with strong association (FDR adjusted P < 0.01 in burden tests) are NBPF20 (OR5.69, 95% CI 2.4-13.5), ERC1 (OR 4.49, 95% CI 2.19-9.23), LOC440434 (OR 1.85, 95% CI 1.32-2.59), GPC5 (OR 1.55, 95% CI 1.21-1.99), and NOTCH2NL(OR 5.46, 95% CI 1.61-18.5). The KEGG pathway analysis shown the 1st and 4th significant pathways are from small cell and non-small cell lung cancer, respectively.
Our analyses led to identification of 32 pathogenic germline rare variants associated with lung cancer susceptibility. However, replication in additional populations is necessary to confirm potential genetic differences in lung cancer risk.
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P2.11 - Screening and Early Detection (ID 178)
- Event: WCLC 2019
- Type: Poster Viewing in the Exhibit Hall
- Track: Screening and Early Detection
- Presentations: 1
- Moderators:
- Coordinates: 9/09/2019, 10:15 - 18:15, Exhibit Hall
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P2.11-07 - Benefits and Harms of Contemporary Lung Cancer Screening: An Infographic to Support Public and Patient Education (ID 1354)
10:15 - 18:15 | Author(s): Paul Brennan
- Abstract
Background
Quantifying and communicating the benefits and harms of low-dose CT (LDCT) lung cancer screening is a complex challenge. Multiple tools have been developed based on the US National Lung Screening Trial (NLST). However, some of these have produced debate and confusion in the public-facing media due to the outdatedness of the NLST protocol and the complexity of the information presented.
Method
We developed a new infographic to represent the benefits and harms of contemporary lung screening. We applied the current US nodule management protocol (Lung-RADS v1.0) to the NLST retrospectively. Across the 3 NLST screens and 4 years of follow-up, we used individual-level data to quantify the number of people per 1000 who would have had (a) all normal results (Lung-RADS categories 1 and 2) without lung cancer; (b) any abnormal results (Lung-RADS 3 and 4A/B/X) without lung cancer; (c) invasive diagnostic procedures without lung cancer; and (d) lung cancer diagnosed. We estimated overdiagnosis using the published NLST estimate (18.5%) and reduced the mortality benefit from screening using the reduction in sensitivity from Lung-RADS (13.3%).
Result
Applying Lung-RADS to NLST, we found that 779 per 1000 people would have had all normal results, 180 any abnormal results without lung cancer, and 41 lung cancer. Among the 180, 13 would have had an invasive procedure, 0.4 (1 in 2500) a major complication, and 0.2 (1 in 5000) death from any cause within 60 days of the procedure. Finally, among 41 lung cancers, 4 represent overdiagnosis and 3 prevented lung cancer deaths. We compiled these results into an infographic (Figure).
Conclusion
Compared with the NLST protocol, modern nodule management reduces harms from screening. Our infographic tool may facilitate communication about lung screening to providers, patients, and the public. It should be updated as additional trial data become available.
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S01 - IASLC CT Screening Symposium: Forefront Advances in Lung Cancer Screening (Ticketed Session) (ID 96)
- Event: WCLC 2019
- Type: Symposium
- Track: Screening and Early Detection
- Presentations: 3
- Now Available
- Moderators:John Kirkpatrick Field, James L Mulshine
- Coordinates: 9/07/2019, 07:00 - 12:00, Colorado Springs (1994)
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S01.06 - Session II: U19 – Implications for the Future Integration of Biomarkers in the Selection of High Risk Individuals for Lung Cancer Screening (ID 3632)
07:00 - 12:00 | Author(s): Paul Brennan
- Abstract
Abstract not provided
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S01.07 - The U19 Plans for Integration of Biomarkers Into Future Lung Cancer Screening (Now Available) (ID 3633)
07:00 - 12:00 | Author(s): Paul Brennan
- Abstract
- Presentation
Abstract
The goal of the U19 Integrative analysis of Lung Cancer Etiology and Risk (INTEGRAL) consortium is to develop biomarkers that characterize individual risk for development and progression from lung cancer. We are using a comprehensive strategy, depicted below in Figure 1, for this analysis and we are drawing on world-wide resources and expertise.
There are three projects focusing on i) genetics of smoking behavior and lung cancer risk, ii) biomarker discovery and validation for identifying individuals at highest risk for developing lung cancer and iii) evaluation of these biomarkers in screening cohorts along with radiographic analaysis to evaluate risk for lung cancer development and nodule behavior. There are also administrative and biostatistics cores.
We will discuss strategies and novel findings from these projects. For Project 1, to assist in genetic analysis, we have reimputed all the available data from lung cancer cases and controls using the haplotype reference consortium to bring together a data lake comprising data from over 100,000 individuals. The consortium provides data to its members and to collaborators who would like to evaluate hypotheses related to lung cancer by providing access for analyses and we currently are supporting 107 projects evaluating lung cancer risk. Additionally, consortium members from the University of Laval have performed transcriptomic analysis of normal lung tissue from over 500 participants undergoing surgery for lung cancer treatment. We are also studying the role that genetic factors have in influencing smoking behavior by collaborating with other large consortia and by studying multiethnic variation using Hawaiian multiethnic populations.
Analyses of the genetic data and further extension to the UK Biobank have identified novel genetic loci that contribute to risk. Interaction analysis of the CHRNA3/A5/B4 cluster with all other genomic regions identifies interactions with the 15q25.1 nicotinic receptors that influence lung cancer risk. Results identified genes in the neuroactive ligand receptor interaction pathway as playing a key role in increasing lung cancer risk. A cross-ethnicity analysis identified genetic factors in the major histocompatibility complex (MHC) that affect risk for lung cancer. We imputed sequence variation for 26,044 cases and 20,836 controls in classical HLA genes, fine-mapped MHC associations for lung cancer risk with major histologies and compared results among ethnicities. Independent and novel associations within HLA genes were identified in Europeans primarily affecting risk for squamous cell histology including amino acids in the HLA-B*0801 peptide binding groove and an independent HLA-DQB1*06 loci group. In Asians, associations are driven by two independent HLA allele sets affecting adenocarcinoma risk primarily that both increase risk in HLA-DQB1*0401 and HLA-DRB1*0701; the latter was better represented by the amino acid Ala-104. These results implicate several HLA-tumor peptide interactions as the major MHC factor modulating lung cancer susceptibility. A rare variant analysis yielded a mutation of the ATM gene that is rare in all populations except individuals of Jewish descent that primarily increase risk for adenocarcinoma and has highest risk in nonsmoking women. Analyses of smoking and genetic data have identified gene-smoking interactions that contribute to lung cancer risk, and particularly several genes that protect at-risk smokers from lung cancer development. Mendelian randomization and mediation analyses are underway to evaluate novel biomarkers that can be further studied in project 2. This effort found a surprising result that elevated levels of vitamin B12 increase risk for lung cancer development.
Project 2 has been bringing together an approach to analyzing biomarkers using data from existing cohort consortia, which have collected samples prior to the clinical presentation of lung cancers. Results of an initial study showed that analysis of 4 circulating proteins (CEA125, CEA, CYFRA 21-1 and pro-SFTB) yielded an area under the receiver operator curve accuracy of 83%. This level of accuracy is sufficient to consider the panel for recruitment of individuals for screening studies, but we anticipate that adding additional biomarkers will further improve the accuracy of risk prediction. Biomarkers that are being further considered include additional protein markers along with micoRNA species, the inclusion of polygenic risk scores and additional serum-derived biomarkers like vitamins B-6 and B-12 that have been shown in mendelian randomization studies to help in identifying high risk subjects.
Project 3 is focused on the establishment and validation of the models in the LDCT screening programs. In collaboration with National Lung Screening Trial, Canadian LDCT screening programs, NELSON and United Kingdom Lung Study (UKLS), we have begun the data harmonization across LDCT studies, including clinic-epidemiological data as well as nodule characteristics. We have established a pipeline of feature extractions for the radiomics analysis and compared the inter-reader variability. The intraclass correlation coefficients are >0.75 for the majority of the radiomics features extracted. We will conduct cross-study validation for the model building to ensure the maximum generalizability of the model. We will start the work on biomarkers and assess their added values in these models.
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S01.19 - Biomarkers (Now Available) (ID 3644)
07:00 - 12:00 | Presenting Author(s): Paul Brennan
- Abstract
- Presentation
Abstract
Improved risk stratification has the potential to enhance the ratio of benefit to harm for lung cancer screening. Risk biomarkers for lung cancer have been identified that have the potential to contribute to risk stratification, and efforts in this area are ongoing, although whether they are practical or cost-effective remains to be clarified. Recent progress in the use of biomarkers for lung cancer risk stratification and their cost-effectiveness will be discussed.
References
Guida F, et al. .Integrative Analysis of Lung Cancer Etiology and Risk (INTEGRAL) Consortium for Early Detection of Lung Cancer, Assessment of Lung Cancer Risk on the Basis of a Biomarker Panel of Circulating Proteins. JAMA Oncol. 2018 Oct 1;4(10)
Robbins HA, et al. .Benefits and harms in the National Lung Screening Trial: expected outcomes with a modern management protocol. Lancet Respir Med. 2019 May 7
Only Members that have purchased this event or have registered via an access code will be able to view this content. To view this presentation, please login, select "Add to Cart" and proceed to checkout. If you would like to become a member of IASLC, please click here.
